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Machine Learning workshop

Machine Learning Workshop

Machine Learning for Engineers workshop

Event Date:                September 13, 2021

Event Time:                10am – Noon (Saudi Time)

Event Address:           Online event (links will be sent via email when you register)

Contact us:                 training@hpc.kaust.edu.sa

Registration

Agenda

The KAUST Supercomputing Core Laboratory (KSL) is organizing a half-day workshop on Machine Learning for Engineers using MATLAB.  This online event is organized in conjunction with CES, exclusive partner of MATLAB & Simulink in the Middle East.

About this event This event will cover the fundamentals of machine learning using MATLAB and will give the participants hands on experience in supervised learning (classification).

Who can attend?

This workshop is open to all engineers, researchers, students and managers, who are working at KAUST or any other educational institute or industrial company in the Middle East.This event is targeted at engineers & researchers who have limited or no experience of applying Deep Learning to their specific problems. Attendees with no background in MATLAB and/or deep learning can certainly benefit from this workshop.

To register

Click here to register for this online workshop. You will be receiving more information via emails after your register.

About the presenter

Flavio Pol is the Senior Application Engineering Manager at CES, the partner of MathWorks in the Middle East. Flavio has more than 7 years of experience in the field of Artificial Intelligence (AI) and is an active researcher on the topic at the University of Sao Paulo, the largest and most prestigious university in Brazil and Latin America. He has worked extensively with a variety of Machine Learning and Deep Learning applications such as Image Classification using CNN, Text Classification using LSTM, Question Answering Systems using Machine Learning algorithms & Fault Classification for predictive maintenance. Nowadays, Flavio is participating on an proprietary advanced research subject for the national oil company in Brazil.

Important: Before attending this workshop

To get the most out of this workshop, we encourage you to do the following free self-paced online certificate, before attending, and/or review the training material from the previous workshop.For more information, visit the workshop website or contact us training@hpc.kaust.edu.sa

Workshop link:

Link sent to the registrants privately

Training material:

Coming soon!

MATLAB download link and instructions (in preparation for this Machine Learning Workshop)

Follow the instructions below to download a 30 day MATLAB trial license with additional toolboxes for the hands-on session on September 13, 2021:

  1. Access the following link  https://www.mathworks.com/campaigns/products/trials.html
  2. Enter your contact information using company or university email. This action will request to create a MathWorks account if you do not have one.
  3. To continue, you need to agree with terms and conditions of the trial license.
  4. At Free MALAB Trial, choose Deep Learning package(image below). Next you will see the list of products within this package(list below). Click Select and continue. If this window for the Deep Learning package does not appear to you, continue with only MATLAB, install it and follow the steps 7 and 8 to install all the listed toolboxes via add-ons.
  5. Download the installer file for the R2020b release for your operating system.
  6. Launch the installer and follow the instructions. If you need additional help, look for the instructions at the documentation: https://www.mathworks.com/help/install/
  7. After the installation, open MATLAB, add more toolboxes to your trial: You can customize your trial using the add-on explorer in MATLAB to select additional toolboxes. Instructions in this link: https://www.mathworks.com/help/matlab/matlab_env/get-add-ons.html
  8. From the Add-ons window, add the following toolboxes: Automated Driving Toolbox, Bioinformatic Toolbox, Fuzzy Logic Toolbox. And you are all set.

If you need installation support, open a ticket with MathWorks at https://www.mathworks.com/support/contact_us.html

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